abstract: The species distribution model DISTRIB was used to model and map potential suitable habitat of ponderosa pine throughout Arizona under current and six future climate scenarios. Importance Values for each climate scenario were estimated from 24 predictor variables consisting of climate, elevation, soil, and vegetation data within a 4 km grid cell. Two emission scenarios, (A2 (high concentration) and B1 (low concentration)) and three climate models (the Parallel Climate Model, the Geophysical Fluid Dynamics Laboratory, and the HadleyCM3) were used to capture the potential variability among future climates and provide a range of responses from ponderosa pine. Summary tables for federal and state managed lands show the potential change in suitable habitat under the different climate scenarios; while an analysis of three elevational regions explores the potential shift of habitat upslope. According to the climate scenarios, mean annual temperature in Arizona could increase by 3.5% while annual precipitation could decrease by 36% over this century. Results of the DISTRIB model indicate that in response to the projected changes in climate, suitable habitat for ponderosa pine could increase by 13% throughout the state under the HadleyCM3 high scenario or lose 1.1% under the average of the three low scenarios. However, the spatial variability of climate changes will result in gains and losses among the ecoregions and federally and state managed lands. Therefore, alternative practices may need to be considered to limit the loss of suitable habitat in areas identified by the models. / Dissertation/Thesis / M.S. Applied Biological Sciences 2011

abstract: This dissertation creates models of past potential vegetation in the Southern Levant during most of the Holocene, from the beginnings of farming through the rise of urbanized civilization (12 to 2.5 ka BP). The time scale encompasses the rise and collapse of the earliest agrarian civilizations in this region. The archaeological record suggests that increases in social complexity were linked to climatic episodes (e.g., favorable climatic conditions coincide with intervals of prosperity or marked social development such as the Neolithic Revolution ca. 11.5 ka BP, the Secondary Products Revolution ca. 6 ka BP, and the Middle Bronze Age ca. 4 ka BP). The opposite can be said about periods of climatic deterioration, when settled villages were abandoned as the inhabitants returned to nomadic or semi nomadic lifestyles (e.g., abandonment of the largest Neolithic farming towns after 8 ka BP and collapse of Bronze Age towns and cities after 3.5 ka BP during the Late Bronze Age). This study develops chronologically refined models of past vegetation from 12 to 2.5 ka BP, at 500 year intervals, using GIS, remote sensing and statistical modeling tools (MAXENT) that derive from species distribution modeling. Plants are sensitive to alterations in their environment and respond accordingly. Because of this, they are valuable indicators of landscape change. An extensive database of historical and field gathered observations was created. Using this database as well as environmental variables that include temperature and precipitation surfaces for the whole study period (also at 500 year intervals), the potential vegetation of the region was modeled. Through this means, a continuous chronology of potential vegetation of the Southern Levantwas built. The produced paleo-vegetation models generally agree with the proxy records. They indicate a gradual decline of forests and expansion of steppe and desert throughout the Holocene, interrupted briefly during the Mid Holocene (ca. 4 ka BP, Middle Bronze Age). They also suggest that during the Early Holocene, forest areas were extensive, spreading into the Northern Negev. The two remaining forested areas in the Northern and Southern Plateau Region in Jordan were also connected during this time. The models also show general agreement with the major cultural developments, with forested areas either expanding or remaining stable during prosperous periods (e.g., Pre Pottery Neolithic and Middle Bronze Age), and significantly contracting during moments of instability (e.g., Late Bronze Age). / Dissertation/Thesis / Ph.D. Geography 2011

Spruce-Fir forests are relicts from the Pleistocene and have migrated back north after the previous warming period as well as up in elevation in the southern Appalachian mountains. This in turn created sky islands of isolated, endemic, and disjunct species. These refugal forests require certain climatic parameters similar to Canada’s boreal mountains but also need additional cloud immersion and precipitation. These forests have experienced stressors in the past, but face continued threats such as air pollution and climate change. Due to limited immigration for the majority of the species on these mountains, a significant number of organisms are at risk of being endangered or extinct. Analyzing the relationships and patterns between species distribution and climatic parameters both in the past and present will help create future prediction maps. These will potentially anticipate where habitat reduction might occur and will benefit management and conservation purposes. The first study will analyze current distributions of Spruce-Fir forests to see which model and variable combination best approximates the unique mountain forests environments. Using the optimal model from the first study, the second study will examine which distributional changes may occur in the future and how these changes compare to paleo-environmental distributions. Anticipated results will show a reduction of habitat in lower peaks with minimal impact at higher peaks based on the known projected trends of cloud ceilings. This research will help with forest and conservation management and will impact a multitude of species that rely on this forest to survive.

Originally endemic to South America, the nine-banded armadillo (Dasypus novemcinctus) has recently expanded its range northward to Illinois. With this range expansion comes concern from both wildlife managers and the general public regarding potential incoming pathogens and unknown impacts on native wildlife. My research, conducted during 2018-2020 in southern Illinois, addressed the following 3 objectives intended to provide information regarding this novel species: (1) test for the presence of Trypanosoma cruzi and Mycobacterium leprae, (2) model the potential distribution of armadillos, and (3) attempt several different armadillo capture methods. For Objective 1, I tested roadkilled specimens for T. cruzi and M. leprae, 2 pathogens known to infect humans, using PCR and ELISA, respectively. All 81 samples tested for T. cruzi and all 25 samples tested for M. leprae were negative. The latter case is consistent with the enemy release hypothesis, suggesting armadillos have evaded parasites present in their native environment due to geographical distance. The absence of T. cruzi in the sampled individuals implies dispersing individuals are more robust than those at the center of their range. For Objective 2, I used MAXENT to model potential armadillo distribution in 51 counties in southern Illinois using 39 presence locations. Modeling identified low-intensity development to be the most important predictor of armadillo presence. For Objective 3, I attempted to capture armadillos using spotlighting on roads, staking out burrows, unbaited single-door cage traps, and unbaited double-door cage traps. Based on trap nights per capture, I found the use of double-door cage traps to be the most efficient method. My study will aid in managing colonizing armadillo populations by presenting information regarding dynamics of disease transmission, predicting areas of armadillo presence, and capture methods.

付記する学位プログラム名: 霊長類学・ワイルドライフサイエンス・リーディング大学院 / 京都大学 / 新制・課程博士 / 博士(理学) / 甲第23406号 / 理博第4741号 / 新制||理||1680(附属図書館) / 京都大学大学院理学研究科生物科学専攻 / (主査)教授 平田 聡, 教授 村山 美穂, 教授 伊谷 原一 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

Few studies utilise modern species distribution data and modeling to make predictions for examining potential fossil localities. Instead, species distribution modeling is often used for palaeoenvironmental interpretations. Using palaeoclimate data to model potential past distributions for a species provides a prediction showing areas where its fossil remains may be found. In this study, the current, Last Glacial Maximum, and Last Interglacial potential distributions of the arid steppe-obligate saiga antelope (Artiodactyla: Bovidae, Saiga tatarica) were modeled using the species distribution model Maxent. Few fossil records exist, but available fossil locality records were used to validate both palaeo models, resulting in speculative predictions about where the saiga may have lived. Known fossil localities of saiga from the Last Glacial Maximum time period were located within predicted moderately suitable environments, while four of seven Last Interglacial fossil localities were located within predicted moderately suitable environments, suggesting that models can accurately identify areas where fossils for the saiga can be found. Specifically, these models suggest saiga fossils may be located in northwestern and northeastern China, the western and central regions of the Middle East, and southern Alaska. The predicted areas in northeastern China are of particular interest because saiga fossils have not been identified in this region, but some palaeontologists theorize that northeast China may have been suitable for saiga in the past. The models lend credence to this argument.

While range-wide population declines have prompted extensive research on greater sage-grouse (Centrocercus urophasianus), basic information about southern periphery populations, such as the Bald Hills population in southern Utah, has not been documented. The objective of this research was to determine habitat preferences and space use patterns of the Bald Hills sage-grouse population which occurs in an area of high potential for renewable energy development. I tracked 66 birds via VHF telemetry in 2011 and 2012 and surveyed vegetation plots throughout the study area. I found that the population was primarily one-stage migratory with seasonal distributions that did not correspond well with previously developed suitable habitat maps (based on local biologist knowledge and lek data) for all seasons; I also found that mean home range sizes ranged from 82 km2 to 157 km2. Nesting hens did not select for any measured vegetation characteristics within the study area, while brood-rearing hens selected for high forb cover. Birds at summer sites (non-reproductive bird locations during the summer season) selected for greater grass and forb cover and lower shrub cover compared with random sites. Overall, Bald Hills sage-grouse used areas with greater shrub canopy cover and lower grass and forb cover than recommended in habitat guidelines. Ten predictor variables were used to model suitable seasonal habitat using Maximum Entropy (maxent). All models were created for the Bald Hills population and projected to the Bureau of Land Management Cedar City Field Office management area and produced excellent model fit (AUC > 0.900). The Bald Hills population had similar nesting and winter habitat preferences as other populations but different brood-rearing and summer habitat preferences. I found local management techniques to be an important driver of seasonal habitat selection; birds selected for areas that had undergone habitat treatments (such as broadcast burn and crushing) within the previous 10 years. My results indicated the Bald Hills periphery population occupies marginal habitat and has adapted unique seasonal habitat preferences. Managers of isolated, fringe, and low-density populations should develop locally specific management guidelines to address the unique adaptations and ensure the persistence of these populations.

Several reports of North American bumble bee (Bombus Latreille) decline have been documented across the continent, but no study has fully assessed the geographic scope of decline. In this study I discuss the importance of Natural History Collections (NHC) in estimating historic bumble bee distributions and abundances, as well as in informing current surveys. To estimate changes in distribution and relative abundance I compare historic data assembled from a >73,000 specimen database with a contemporary 3-year survey of North American bumble bees across 382 locations in the contiguous U.S.A. Based on my results, four historically abundant bumble bees, B. affinis, B. occidentalis, B. pensylvanicus and B. terricola, have declined by 72 - 96% relative abundance across their native distribution, while B. bifarius, B. bimaculatus, B. impatiens, and B. vosnesenskii appear to be relatively stable. Finally, I provide some notes on the distribution, abundance, and frequency of Nosema bombi infections in Alaskan B. occidentalis.

The developments of species distribution modeling techniques have brought new opportunities in the field of biological invasion management. In particular, statistical niche modeling for spatio-temporal predictions of species’ distribution is a widely spread tool that has proved its efficiency. The main purpose of this Master thesis is to study applicability of species distribution modeling to invasive alien species, with the aim of supporting efficient decision-making for their prevention. Some research questions are: how useful can species distribution modeling be for invasives’ prevention? Is distribution modeling technically feasible in the case of invasive species? What types of techniques are recommended to model distributions of IAS? What are the limits of such a tool? The methods employed to answer these questions are literature review and expert advice. I found that species distribution models can provide risk maps which are necessary to enable effective invasive alien species’ prevention. However intrinsic characteristics of invasives introduce uncertainties in the predictions made. Consequently several preliminary analyses should be conducted before applying the distribution model. Finally recommendations were made on the most appropriate distribution modeling technique to use depending on the urgency of the situation and the availability of data. / Utvecklingen av metoder för modelering av artdistribution har medfört nya möjligheter inom området hantering av biologiska invasioner. Statistisk nischmodelering för spatio-temporala förutsägelser av arters distribution är ett väl använt verktyg som har visat sig vara effektivt. Det övergripande målet med det här arbetet har varit att studera hur lämpad artmodelering är vid förebyggande av invasioner av främmande arter. Det har även undersökts huruvida metoden kan bidra till bättre och enklare beslutsfattande när det kommer till att förhindra sådana invasioner. Forskningsfrågorna lyder: hur användbart är fördelningsmodelering för förebyggande av spriding av invasiva arter? Är distributionsmodelering tekniskt genomförbar när det gäller invasiva arter? Vilka olika tekniker rekommenderas för att modelera spridningen av invasiva arter? Vilka begräsningar har modelerna? De metoder som används är litteraturöversikt och expertråd. Resultaten visar att artdistributionsmodelering kan bidra till att sammanställa riskkartor som är nödvändiga för att möjliggöra ett förebyggande arbete. Men speciella egenskaper hos de invasiva arterna som är svåra att förutse skapar osäkerheter i resultatet. Därför kan preliminära analyser med fördel genomföras innan modelering. I slutsatserna återfinns rekommendationer för vilken distributionsmodelteknik man bör använda, beroende av hur brådskande situationen är och om data finns tillgängligt.

Spatial information about invasive species abundance is critical for estimating impact and understanding risk to ecosystems and economies. Unfortunately, at landscape and regional scales, most distribution datasets provide limited information about abundance. However, national and regional invasive plant occurrence datasets are increasingly available and spatially extensive. We aim to test whether the frequency of these point occurrences can be used as a proxy for abundance of invasive plants. We compiled both occurrence and abundance data for nine regionally important invasive plants in the northeast US using a combination of herbarium records, surveys of expert knowledge, and various invasive species spatial databases. We integrated all available abundance information based on infested area, percent cover, or qualitative descriptions into abundance rankings ranging from 0 (absent) to 4 (highly abundant). Within equal area grid cells of 800 m, we counted numbers of occurrence points and used an ordinal regression to test whether higher numbers of occurrence points were positively correlated with abundance rankings. We compiled a total 49,341 occurrence points in 18,533 cells, of which 12,183 points (25%) within 4,278 cells (32%) had associated abundance information. In six of nine study species we found slight but significant positive overall relationships between abundance rank and occurrence frequency at high abundance ranks. However, at low abundance rankings the relationship tended to be negative and the magnitude of the overall difference in occurrence frequency was too small to be relevant to management. My results suggest that currently available occurrence datasets are unlikely to serve as effective proxies for abundance, and models derived from invasive plant occurrence datasets should not be interpreted as indicative of plant abundance and associated impact. Increased efforts to collect and report invasive species abundance information, and/or higher densities of occurrence points in heavily infested areas are strongly needed for regional scale assessments of potential abundance and associated impact.